Journal of the Korean Society of Safety (한국안전학회지)

The Korean Society of Safety (한국안전학회)
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A Study on the Optimization of Offsite Consequence Analysis by Plume Segmentation and Multi-Threading

플룸분할 및 멀티스레딩을 통한 소외사고영향 분석시간 최적화 연구

  • Seunghwan, Kim (Risk Assessment Research Team, Korea Atomic Energy Research Institute) ;
  • Sung-yeop, Kim (Risk Assessment Research Team, Korea Atomic Energy Research Institute)
  • 김승환 (한국원자력연구원 리스크평가연구실) ;
  • 김성엽 (한국원자력연구원 리스크평가연구실)
  • Received : 2022.11.29
  • Accepted : 2022.12.22
  • Published : 2022.12.31
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Abstract

A variety of input parameters are taken into consideration while performing a Level 3 PSA. Some parameters related to plume segments, spatial grids, and particle size distribution have flexible input formats. Fine modeling performed by splitting a number of segments or grids may enhance the accuracy of analysis but is time-consuming. Analysis speed is highly important because a considerably large number of calculations is required to handle Level 2 PSA scenarios for a single-unit or multi-unit Level 3 PSA. This study developed a sensitivity analysis supporting interface called MACCSsense to compare the results of the trials of plume segmentation with the results of the base case to determine its impact (in terms of time and accuracy) and to support the development of a modeling approach, which saves calculation time and improves accuracy. MACCSense is an automation tool that uses a large amount of plume segmentation analysis results obtained from MUST Converter and Mr. Manager developed by KAERI to generate a sensitivity report that includes impact (time and accuracy) by comparing them with the base-case result. In this study, various plume segmentation approaches were investigated, and both the accuracy and speed of offsite consequence analysis were evaluated using MACCS as a consequence analysis tool. A simultaneous evaluation revealed that execution time can be reduced using multi-threading. In addition, this study can serve as a framework for the development of a modeling strategy for plume segmentation in order to perform accurate and fast offsite consequence analyses.

Keywords

Acknowledgement

This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT: Ministry of Science, ICT) (No. RS-2022-00144405).

References

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